Article

Epidemiology: Dimensions of Superspreading

University of Oxford, Oxford, England, United Kingdom
Nature (Impact Factor: 41.46). 12/2005; 438(7066):293-5. DOI: 10.1038/438293a
Source: PubMed

ABSTRACT

Analyses of contact-tracing data on the spread of infectious disease, combined with mathematical models, show that control measures require better knowledge of variability in individual infectiousness.

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    • "Comparison of a new real-time quantitative PCR (qPCR) which is specific for the envelope gene's transmembrane region has been done with a competitive ELISA (cELISA). Such comparative test has led to the conclusion that qPCR may be used as a supplemental tool for diagnosis and for measuring the load of the virus [71, 145]. "
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    ABSTRACT: Irrespective of aetiology, infectious respiratory diseases of sheep and goats contribute to 5.6 percent of the total diseases of small ruminants. These infectious respiratory disorders are divided into two groups: the diseases of upper respiratory tract, namely, nasal myiasis and enzootic nasal tumors, and diseases of lower respiratory tract, namely, peste des petits ruminants (PPR), parainfluenza, Pasteurellosis, Ovine progressive pneumonia, mycoplasmosis, caprine arthritis encephalitis virus, caseous lymphadenitis, verminous pneumonia, and many others. Depending upon aetiology, many of them are acute and fatal in nature. Early, rapid, and specific diagnosis of such diseases holds great importance to reduce the losses. The advanced enzyme-linked immunosorbent assays (ELISAs) for the detection of antigen as well as antibodies directly from the samples and molecular diagnostic assays along with microsatellites comprehensively assist in diagnosis as well as treatment and epidemiological studies. The present review discusses the advancements made in the diagnosis of common infectious respiratory diseases of sheep and goats. It would update the knowledge and help in adapting and implementing appropriate, timely, and confirmatory diagnostic procedures. Moreover, it would assist in designing appropriate prevention protocols and devising suitable control strategies to overcome respiratory diseases and alleviate the economic losses.
    Full-text · Article · Jun 2014 · Veterinary Medicine International
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    • "A patient who travels away from home to low-lying areas where malaria is endemic might have the most probable effect on malaria spatiotemporal patterns in high-altitude villages. Travel often increases exposure to infectious disease and can affect disease prevention and control efforts [36]. Travel has also contributed to the global spread of malaria during the history of humankind [37]. "
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    ABSTRACT: Background Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Methods Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Results Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. Conclusion The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.
    Full-text · Article · Jun 2014 · Malaria Journal
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    • "Interestingly, the percentage of superemitters (19%) fits the proposed 20/80 rule, suggesting that roughly 20% of the most infectious individuals are responsible for 80% of infections [21]. Although this rule has not proven for influenza virus transmission, the concept of heterogeneity in infectiousness should be considered because it has been demonstrated in severe acute respiratory syndrome [21, 22]. Targeting superemitters to control transmission may also be a more effective and efficient alternative to the broad approach that targets all patients with in- fluenza [22]. "
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    ABSTRACT: Background: Defining dispersal of influenza virus via aerosol is essential for the development of prevention measures. Methods: During the 2010-2011 influenza season, subjects with influenza-like illness were enrolled in an emergency department and throughout a tertiary care hospital, nasopharyngeal swab specimens were obtained, and symptom severity, treatment, and medical history were recorded. Quantitative impaction air samples were taken not ≤0.305 m (1 foot), 0.914 m (3 feet), and 1.829 m (6 feet) from the patient's head during routine care. Influenza virus was detected by rapid test and polymerase chain reaction. Results: Sixty-one of 94 subjects (65%) tested positive for influenza virus. Twenty-six patients (43%) released influenza virus into room air, with 5 (19%) emitting up to 32 times more virus than others. Emitters surpassed the airborne 50% human infectious dose of influenza virus at all sample locations. Healthcare professionals (HCPs) were exposed to mainly small influenza virus particles (diameter, <4.7 µm), with concentrations decreasing with increasing distance from the patient's head (P < .05). Influenza virus release was associated with high viral loads in nasopharyngeal samples (shedding), coughing, and sneezing (P < .05). Patients who reported severe illness and major interference with daily life also emitted more influenza virus (P < .05). Conclusions: HCPs within 1.829 m of patients with influenza could be exposed to infectious doses of influenza virus, primarily in small-particle aerosols. This finding questions the current paradigm of localized droplet transmission during non-aerosol-generating procedures.
    Preview · Article · Jan 2013 · The Journal of Infectious Diseases
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